Optimization

This book provides a comprehensive examination of the structure of approximate optimal policies in Markov decision processes (MDPs) with finite state spaces, as well as approximate optimal solutions for deterministic discrete-time optimal control problems.

This book provides a practical and rewarding path for early to mid-career professionals of all disciplines (STEM and non-STEM) to develop the intentional mental practice of Systems Thinking together with Rigorous Methods that improve the way we view, contemplate, approach and deal with complex challenges.

This book offers an extensive guide to understanding, implementing, and applying the Bees Algorithm, a powerful nature-inspired optimisation metaheuristic that mimics the foraging behaviour of honey bees.

This book offers an extensive guide to understanding, implementing, and applying the Bees Algorithm, a powerful nature-inspired optimisation metaheuristic that mimics the foraging behaviour of honey bees.

This book provides a practical and rewarding path for early to mid-career professionals of all disciplines (STEM and non-STEM) to develop the intentional mental practice of Systems Thinking together with Rigorous Methods that improve the way we view, contemplate, approach and deal with complex challenges.

This book presents solutions to various extremal problems in analysis and provides mathematical tools that can be used to solve complex problems in different areas of fundamental and applied science.

The aim of this book is to present a self-contained account of discrete weak KAM theory.

The aim of this book is to present a self-contained account of discrete weak KAM theory.

This book focuses on recent advances in and applications of constrained and nonlinear control.

This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content.

This book is a research monograph with specialized mathematical preliminaries.

This book is a research monograph with specialized mathematical preliminaries.

This book focuses on recent advances in and applications of constrained and nonlinear control.

This book presents solutions to various extremal problems in analysis and provides mathematical tools that can be used to solve complex problems in different areas of fundamental and applied science.

This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content.

Borel Games are multiplayer games with infinite horizon and general payoff functions.

Borel Games are multiplayer games with infinite horizon and general payoff functions.

Convex Analysis in Polynomial Spaces with Applications is intended to serve a broad audience of undergraduate and graduate students, junior and senior researchers, and as a general self-study guide for anyone who wishes to get acquainted with geometry of Banach spaces of polynomials with applications.

Convex Analysis in Polynomial Spaces with Applications is intended to serve a broad audience of undergraduate and graduate students, junior and senior researchers, and as a general self-study guide for anyone who wishes to get acquainted with geometry of Banach spaces of polynomials with applications.

The book consists of the proceedings of the workshop "e;New Trends and Challenges in Optimization Theory Applied to Space Engineering"e;, held in l'Aquila (Italy), and organized by the Gran Sasso Science Institute (GSSI), on December 13-15, 2023.

This book explores mathematical modeling, predictive analytics, and interdisciplinary tools in formulating, implementing, and evaluating industrial strategies.

This book explores mathematical modeling, predictive analytics, and interdisciplinary tools in formulating, implementing, and evaluating industrial strategies.

This book is based on lectures given at the Mathematisches Forschungsinstitut Oberwolfach on “Computational Variational Flows in Machine Learning and Optimal Transport”.

This book offers as exploration into the emerging field of Inverse Combinatorial Optimization Problems (ICOPs), a transformative area within operations research.

The book consists of the proceedings of the workshop "e;New Trends and Challenges in Optimization Theory Applied to Space Engineering"e;, held in l'Aquila (Italy), and organized by the Gran Sasso Science Institute (GSSI), on December 13-15, 2023.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2023), which was held at Universitat Hamburg, Germany, August 29-September 1, 2023.

This book offers as exploration into the emerging field of Inverse Combinatorial Optimization Problems (ICOPs), a transformative area within operations research.

This book is based on lectures given at the Mathematisches Forschungsinstitut Oberwolfach on “Computational Variational Flows in Machine Learning and Optimal Transport”.

This proceedings volume convenes revised, selected works presented at the 3rd International Seminar on Computing Technologies and Applied Mathematics (CTAM2024), held at Komsomolsk-na-Amure State University, Russia, from October 7 to 11, 2024.

This book LNCS 15681 constitutes the refereed proceedings of the 24th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2025, held in Novosibirsk, Russia, during July 7–11, 2025.

This book LNCS 15681 constitutes the refereed proceedings of the 24th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2025, held in Novosibirsk, Russia, during July 7–11, 2025.

This book offers a comprehensive exploration of the dynamic intersection between geometry and optimization.

This proceedings volume convenes revised, selected works presented at the 3rd International Seminar on Computing Technologies and Applied Mathematics (CTAM2024), held at Komsomolsk-na-Amure State University, Russia, from October 7 to 11, 2024.

This book provides a novel and unifying perspective on the structural properties of fair solutions in optimization formulations.

This book examines the sustainable supply chain of renewable energy networks, combining global perspectives with engineering optimization.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2023), which was held at Universitat Hamburg, Germany, August 29-September 1, 2023.

This book presents three short courses on topics at the intersection of Calculus of Variations, PDEs and Material Science, based on lectures given at the CIME summer school “Variational and PDE Methods in Nonlinear Science”, held in Cetraro (Italy), July 10–14, 2023.

This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning.

This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning.

This book is concerned with optimal control problems of dynamical systems described by partial differential equations (PDEs).

This book delves into the intricate world of fixed point theory, focusing on the Krasnoselskii-Mann method to tackle common fixed point problems within a finite family of quasi-nonexpansive mappings in hyperbolic metric spaces.

This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how their combined use efficiently solves large-scale optimization problems relevant to engineering, particularly in electrical, and industrial engineering, with a focus on energy.

This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how their combined use efficiently solves large-scale optimization problems relevant to engineering, particularly in electrical, and industrial engineering, with a focus on energy.

This book introduces an optimal iterative learning control (ILC) design framework from the end user's point of view.

This book introduces an optimal iterative learning control (ILC) design framework from the end user's point of view.

This book delves into the intricate world of fixed point theory, focusing on the Krasnoselskii-Mann method to tackle common fixed point problems within a finite family of quasi-nonexpansive mappings in hyperbolic metric spaces.

This book explores the application of machine learning-based methods, particularly Bayesian optimization, within the realm of laser-plasma accelerators.

This book introduces a real-time optimization (RTO) method based on the dynamic correlation integration (DCI) theory, which has the performances of modeling-free and self-adaptive model changes in real process.